2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2018
DOI: 10.1109/embc.2018.8513021
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Segmentation of cervical nuclei using SLIC and pairwise regional contrast

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Cited by 7 publications
(2 citation statements)
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“…Saha et al [15,16] used fuzzy c-means clustering constrained by a Circular Shape Function (CSF) to detect a nucleus. Later on, Saha et al [17] also proposed a method of segmenting cervical nuclei by merging the oversegmented SLIC superpixel regions based on pairwise regional contrast and image gradient contour evaluations. Their more recent work [18] proposes to segment nuclei by merging superpixels generated by the statistical region merging (SRM) algorithm using pairwise regional contrasts and gradient boundaries.…”
Section: Introductionmentioning
confidence: 99%
“…Saha et al [15,16] used fuzzy c-means clustering constrained by a Circular Shape Function (CSF) to detect a nucleus. Later on, Saha et al [17] also proposed a method of segmenting cervical nuclei by merging the oversegmented SLIC superpixel regions based on pairwise regional contrast and image gradient contour evaluations. Their more recent work [18] proposes to segment nuclei by merging superpixels generated by the statistical region merging (SRM) algorithm using pairwise regional contrasts and gradient boundaries.…”
Section: Introductionmentioning
confidence: 99%
“…Fatigue-and experience-induced failures always occur and result in low operation success rates and large damage, thus degrading the performance of intracellular manipulation [22,23]. Generally, intracellular objects are fragile [24,25] and usually have irregular shapes [26,27], distribution [28,29], and small sizes [30,31]. For example, mitochondria in mammalian animals are usually less than 2 µm and randomly distribute among the cytoplasm [32].…”
Section: Introductionmentioning
confidence: 99%